Human Interaction Proofs (HIPs), or Completed Automated Public Turing tests to tell Computers and Humans Apart (CAPTCHAs), referred to jointly herein as HIPs, are known solutions for allowing computers and computer-based devices, e.g., internet servers running a webmail, i.e., web-based email, service, hand-held devices, computer-based cell phones, etc., collectively referred to herein as computing devices, to attempt to distinguish between other computing devices running automated programs and humans. HIPs provide filters that are used to prevent automated programs from utilizing computing services intended for humans. Such automated scripts, if successful, have measureable negative effects on the computing service, whether due to abuse or resource expenditure.
In general HIPs are software programs that can generate and grade tests that humans can be expected to pass and automated computing device programs can be expected to fail, allowing a computing device system to differentiate between a human access and a computing device running automated programs, e.g., bots. Bots are software applications that run automated tasks over the internet, including, e.g., attempting to automatically open email accounts for unwarranted purposes such as disseminating SPAM emails and participating in voting or rating contests or activities to unduly influence the outcome, automatically open accounts on folder-shares for surreptitiously acquiring unwarranted disk space allocations, and automatically reserve high quantities of domains that can potentially be sold to legitimate companies for high prices.
While there are many HIP designs, reading-based HIP challenges are currently some of the most popularly implemented. The most commonly employed reading-based HIPs are composed of characters rendered to an image and distorted, or otherwise obfuscated, before being presented to a user. A user, whether human or computing device, must first identify all the characters in the HIP, in the correct order, before being granted access to the desired computing service.
The success rate is important for breaking, i.e., solving for unwarranted purposes, HIPs since it reduces the cost of automatic trials. HIPs, or HIP challenges, that are too difficult, or costly, for bots to break can be solved by forwarding the HIP to humans in countries where human labor is cheap. It is estimated that shipping via the internet, e.g., farming, HIPs to sweatshops, or Turing Farms, can currently reduce the costs of breaking HIPs to as low as sixty cents an hour, implying approximately 0.17 cents per HIP solution. Estimates today attest to humans around the world breaking approximately sixty million HIPs every day. And as humans are solving the HIPs there is no known unbreakable HIP challenge design that will still enable legitimate human users the ability to solve them and access the desired computing services.
Additionally, bots for breaking HIPs are becoming more technologically savvy and capable of increasingly breaking more HIPs. One known solution to combat smarter bots is to design the HIP challenges to be increasingly more difficult to solve. This solution, however, has the unfortunate, and unwanted, effect of generating HIPs that are becoming more difficult for legitimate humans to solve. Computing services that more regularly fail legitimate human attempted access will have decreased user satisfaction, and, commensurately, decreased use.
Thus, it would be desirable to design a system and methodology for implementing Active HIPs that will continue to allow legitimate human users quick and successful resolution to the problem displayed by the Active HIP. It would also be desirable for these Active HIPs to, at the same time, block bots and Turing Farms from easily and/or cost effectively breaking these same HIPs.